
Filter News
Area of Research
- Advanced Manufacturing (10)
- Biology and Environment (35)
- Computational Engineering (1)
- Computer Science (2)
- Energy Science (99)
- Fusion and Fission (8)
- Isotope Development and Production (1)
- Isotopes (24)
- Materials (57)
- Materials for Computing (12)
- National Security (29)
- Neutron Science (22)
- Nuclear Science and Technology (9)
- Quantum information Science (3)
- Supercomputing (86)
News Type
News Topics
- (-) 3-D Printing/Advanced Manufacturing (104)
- (-) Cybersecurity (31)
- (-) Frontier (60)
- (-) Isotopes (53)
- (-) Machine Learning (50)
- (-) Microscopy (40)
- (-) Polymers (22)
- (-) Space Exploration (16)
- (-) Summit (62)
- (-) Transportation (56)
- Advanced Reactors (24)
- Artificial Intelligence (112)
- Big Data (53)
- Bioenergy (93)
- Biology (106)
- Biomedical (59)
- Biotechnology (35)
- Buildings (45)
- Chemical Sciences (70)
- Clean Water (18)
- Composites (23)
- Computer Science (174)
- Coronavirus (36)
- Critical Materials (16)
- Education (5)
- Element Discovery (1)
- Emergency (3)
- Energy Storage (75)
- Environment (154)
- Exascale Computing (64)
- Fossil Energy (7)
- Fusion (54)
- Grid (48)
- High-Performance Computing (113)
- Hydropower (6)
- ITER (6)
- Materials (111)
- Materials Science (111)
- Mathematics (8)
- Mercury (9)
- Microelectronics (4)
- Molten Salt (5)
- Nanotechnology (46)
- National Security (78)
- Neutron Science (136)
- Nuclear Energy (94)
- Partnerships (67)
- Physics (60)
- Quantum Computing (48)
- Quantum Science (79)
- Security (28)
- Simulation (52)
- Software (1)
- Statistics (3)
Media Contacts

Two-and-a-half years after breaking the exascale barrier, the Frontier supercomputer at the Department of Energy’s Oak Ridge National Laboratory continues to set new standards for its computing speed and performance.

Researchers used the world’s fastest supercomputer, Frontier, to train an AI model that designs proteins, with applications in fields like vaccines, cancer treatments, and environmental bioremediation. The study earned a finalist nomination for the Gordon Bell Prize, recognizing innovation in high-performance computing for science.

Researchers with the Department of Energy’s Oak Ridge National Laboratory and Sierra Space Corporation have developed a new silicon-carbide-based thermal protection system, or TPS, for reusable commercial spacecraft.

Researchers at Oak Ridge National Laboratory used the Frontier supercomputer to train the world’s largest AI model for weather prediction, paving the way for hyperlocal, ultra-accurate forecasts. This achievement earned them a finalist nomination for the prestigious Gordon Bell Prize for Climate Modeling.

A research team led by the University of Maryland has been nominated for the Association for Computing Machinery’s Gordon Bell Prize. The team is being recognized for developing a scalable, distributed training framework called AxoNN, which leverages GPUs to rapidly train large language models.

The Department of Energy has awarded an $88.8 million contract to Hensel Phelps for the construction of a facility to enrich stable isotopes at Oak Ridge National Laboratory.

Larry Seiber, an R&D staff member in the Vehicle Power Electronics group at the Department of Energy’s Oak Ridge National Laboratory, has been elevated to senior member of the Institute of Electrical and Electronics Engineers.

A multi-institutional team of researchers led by the King Abdullah University of Science and Technology, or KAUST, Saudi Arabia, has been nominated for the Association for Computing Machinery’s 2024 Gordon Bell Prize for Climate Modelling.

Researchers led by the University of Melbourne, Australia, have been nominated for the Association for Computing Machinery’s 2024 Gordon Bell Prize in supercomputing for conducting a quantum molecular dynamics simulation 1,000 times greater in size and speed than any previous simulation of its kind.

ORNL and NASA co-hosted the fourth iteration of this invitation-only event, which brings together geospatial, computational, data and engineering experts around a theme. This year’s gathering focused on how artificial intelligence foundation models can enable geospatial digital twins.